Method for estimating distance to an object via a vehicular vision system

ABSTRACT

A method for estimating distance to an object via a vehicular vision system includes disposing a camera at a vehicle so as to view at least exterior of the vehicle. An ECU is provided that includes an image processor. Multiple frames of image data are captured via the camera while the vehicle is moving, and are provided to the ECU. The provided captured frames of image data are processed to determine a three dimensional object present in a field of view of the camera, and a point of interest is determined on the determined object. An estimated location in three dimensional space of the determined point of interest relative to the vehicle is determined, and distance to the estimated location is estimated by comparing provided captured frames of image data where there is movement of the determined point of interest of the determined object relative to the camera.

CROSS REFERENCE TO RELATED APPLICATIONS

The present application is a continuation of U.S. patent applicationSer. No. 14/969,527, filed Dec. 15, 2015, now U.S. Pat. No. 10,713,506,which claims the filing benefits of U.S. provisional application Ser.No. 62/093,743, filed Dec. 18, 2014, which is hereby incorporated hereinby reference in its entirety.

FIELD OF THE INVENTION

The present invention relates generally to a vehicle vision system for avehicle and, more particularly, to a vehicle vision system that utilizesone or more cameras at a vehicle.

BACKGROUND OF THE INVENTION

Use of imaging sensors in vehicle imaging systems is common and known.Examples of such known systems are described in U.S. Pat. Nos.5,949,331; 5,670,935 and/or 5,550,677, which are hereby incorporatedherein by reference in their entireties.

SUMMARY OF THE INVENTION

The present invention provides a collision avoidance system or visionsystem or imaging system for a vehicle that utilizes one or more cameras(preferably one or more CMOS cameras) to capture image datarepresentative of images exterior of the vehicle, and, responsive toimage processing of captured image data, provides distance estimation toobjects exterior of the vehicle.

The present invention provides reliable distance estimation for detectedobjects. Typically, for a moving ego vehicle and static targets,structure from motion (SfM) is used for estimating the depth of theobjects. SfM is typically computed over a pair of frames and the outputdepth is then post-processed. However, given the relatively low amountof motion and different degree of motion along different optical axes,the reliability of SfM varies. Particularly for wide field of view (FOV)optics (such as fish-eye lenses), the use of SfM is limited to about 3meters in range and is very limited along the central area of the imagewhere the motion flow would be along the optical axis for front and rearcameras.

The method of the present invention helps alleviate the reliabilityproblem by first using the available frame data in a more structuredenvironment to get more stable outputs as well as using someback-projection to reject bad or unstable outputs.

This technique is moving towards reliable depth estimation that may becompetitive with camera systems with the ultrasonic sensors but with agreater range of estimation. The system of the present invention is notonly applicable to wide angle optics but also to narrow angle FOVcameras, such as may be used in the side exterior rearview mirrors forlane watch or such as may be used at the vehicle windshield.

These and other objects, advantages, purposes and features of thepresent invention will become apparent upon review of the followingspecification in conjunction with the drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a plan view of a vehicle with a vision system thatincorporates cameras in accordance with the present invention;

FIG. 2 shows a vehicle at an intersection and shows an image captured bya camera of the vehicle;

FIG. 3 shows images captured by a side camera using a fish-eye lens;

FIG. 4 shows a 3D point registration description suitable for use withthe present invention;

FIG. 5 shows equations for determining a 3D point position;

FIG. 6 shows the 3D point registration using an initialization of DE ofa point of interest in accordance with the present invention;

FIGS. 7 and 8 show how the initial estimate is refined in accordancewith the present invention;

FIGS. 9 and 10 show optional steps for iterative refinement of the 3Dreconstruction of the present invention; and

FIGS. 11 and 12 show the steps of recursive updating of the estimates toupdate a quality measure of the 3D point reconstruction in accordancewith the present invention.

DESCRIPTION OF THE PREFERRED EMBODIMENTS

A vehicle vision system and/or driver assist system and/or objectdetection system and/or alert system operates to capture images exteriorof the vehicle and may process the captured image data to display imagesand to detect objects at or near the vehicle and in the predicted pathof the vehicle, such as to assist a driver of the vehicle in maneuveringthe vehicle in a rearward direction. The vision system includes an imageprocessor or image processing system that is operable to receive imagedata from one or more cameras and provide an output to a display devicefor displaying images representative of the captured image data.Optionally, the vision system may provide a top down or bird's eye orsurround view display and may provide a displayed image that isrepresentative of the subject vehicle, and optionally with the displayedimage being customized to at least partially correspond to the actualsubject vehicle.

Referring now to the drawings and the illustrative embodiments depictedtherein, a vehicle 10 includes an imaging system or vision system 12that includes at least one exterior facing imaging sensor or camera,such as a rearward facing imaging sensor or camera 14 a (and the systemmay optionally include multiple exterior facing imaging sensors orcameras, such as a forwardly facing camera 14 b at the front (or at thewindshield) of the vehicle, and a sidewardly/rearwardly facing camera 14c, 14 d at respective sides of the vehicle), which captures imagesexterior of the vehicle, with the camera having a lens for focusingimages at or onto an imaging array or imaging plane or imager of thecamera (FIG. 1). The vision system 12 includes a control or electroniccontrol unit (ECU) or processor 18 that is operable to process imagedata captured by the cameras and may provide displayed images at adisplay device 16 for viewing by the driver of the vehicle (althoughshown in FIG. 1 as being part of or incorporated in or at an interiorrearview mirror assembly 20 of the vehicle, the control and/or thedisplay device may be disposed elsewhere at or in the vehicle). The datatransfer or signal communication from the camera to the ECU may compriseany suitable data or communication link, such as a vehicle network busor the like of the equipped vehicle.

Surround awareness and driver assistance is a key marketable feature forvehicles. Generic object detection using a fish eye camera is one suchfeature. Distance estimation in the scene needed to add value toexisting detection based algorithms (such as, for example, objectdetection (OD), blind spot detection (BSD), Automatic parking spotdetection and/or the like). The distance estimation may act as astand-alone distance estimation feature. Distance estimation is atriangulation-based SfM problem, which requires the information on (i)correspondent feature points in consecutive images and (ii) cameraparameters at each viewpoint of a moving camera. Most past developmentcentered around distance estimation using solving triangulation problemsand bundle adjustment for refinement of estimates.

Use of fish-eye optics or lenses on vehicular cameras may haveassociated difficulties. There is an increase in the use of fish-eyeoptics with the developing market interest in smart surround viewsystems. The features cannot be measured exactly in these fish-eyeimages, and this leads to a loss in accuracy of distance estimation ofpoints of interest. Such fish-eye optics thus createperformance/robustness issues since the variations possible in thedistance estimation due to the inaccurate measurement of image featuresin these images. In an image captured by use of a fish-eye lens, thefeatures not only vary in size, but also in orientation.

The present invention provides a three dimensional (3D) pointregistration process to determine distances to objects present in thefield of view of the camera. To mitigate the effect of inconsistentdistance estimation of points of interest, a 3D point registrationstrategy of the present invention may be implemented. Utilizing the apriori knowledge about the optics and extrinsic orientation of thecamera, the system may get an initial 3D reconstruction of points ofinterest (POIs) from current image feature pairs by solving atriangulation problem. The system may measure the reliability/quality ofcurrent 3D reconstruction by re-projecting the 3D POIs into an imageplane. The system may refine the 3D reconstruction of POIs by weightedaverage when more than one reconstruction is available. The weightingfactor is related to the reliability/quality measure of its 3Dreconstruction using individual image feature pairs. Optionally, thesystem may provide iterative refinement of the 3D reconstruction byrepeating the following steps until no improvement can be achieved. Thesteps include (a) refining the correspondent feature locations bycomparing the similarity between the projected and the detectedfeatures, (b) selecting the corresponding features according to theirsimilarity measurement, (c) repeating the 3D reconstruction by solvingtriangulation problem from newly selected corresponding pairs, and (d)determining a weighted average of all 3D reconstructions that yields 3Dreconstructions of POIs.

As shown in the figures, the system of the present invention detectsdistinguished features (POIs) of a determined three dimensional objectin each frame of captured image data and performs a correspondenceanalysis to find matched point pairs. Using a triangulation method, aninitial estimate of a determined point may be found from thecorrespondent feature pair. The system may measure the quality of the 3Dpoint reconstruction. The initial estimate of the point may be refinedvia further correspondence analysis and projections. The iterativerefinement may be repeated until no improvement is achieved or little orno significant improvement is achieved (i.e., when the improvement isbelow a threshold level between iterations).

Thus, given two or more images and the corresponding camera geometry andposition information, the system determines a 3D position of a point ofinterest (x, y, z) on an object. The similarity between the projectedfeature points on two image planes (as the vehicle moves relative to theobject) may be maximized (see FIG. 5). As shown in FIG. 6, the systemthus may detect distinguishing features or points of interest (POIs) ineach frame and perform correspondence analysis to find matched pointpairs (where the POI is in each of the frames of captured image data).The triangulation method is used to find an initial estimate of the 3Dpoint location from the corresponding feature pair. The quality of the3D point location reconstruction may then be measured.

As shown in FIGS. 7-10, when a third image plane is provided, theinitial estimate of the 3D point location may be refined. As shown inFIGS. 11-12, the estimates may be updated as additional images areprovided.

The camera or sensor may comprise any suitable camera or sensor.Optionally, the camera may comprise a “smart camera” that includes theimaging sensor array and associated circuitry and image processingcircuitry and electrical connectors and the like as part of a cameramodule, such as by utilizing aspects of the vision systems described inInternational Publication Nos. WO 2013/081984 and/or WO 2013/081985,which are hereby incorporated herein by reference in their entireties.

The system includes an image processor operable to process image datacaptured by the camera or cameras, such as for detecting objects orother vehicles or pedestrians or the like in the field of view of one ormore of the cameras. For example, the image processor may comprise anEYEQ2 or EYEQ3 image processing chip available from Mobileye VisionTechnologies Ltd. of Jerusalem, Israel, and may include object detectionsoftware (such as the types described in U.S. Pat. Nos. 7,855,755;7,720,580 and/or 7,038,577, which are hereby incorporated herein byreference in their entireties), and may analyze image data to detectvehicles and/or other objects. Responsive to such image processing, andwhen an object or other vehicle is detected, the system may generate analert to the driver of the vehicle and/or may generate an overlay at thedisplayed image to highlight or enhance display of the detected objector vehicle, in order to enhance the driver's awareness of the detectedobject or vehicle or hazardous condition during a driving maneuver ofthe equipped vehicle.

The vehicle may include any type of sensor or sensors, such as imagingsensors or radar sensors or lidar sensors or ladar sensors or ultrasonicsensors or the like. The imaging sensor or camera may capture image datafor image processing and may comprise any suitable camera or sensingdevice, such as, for example, a two dimensional array of a plurality ofphotosensor elements arranged in at least 640 columns and 480 rows (atleast a 640×480 imaging array, such as a megapixel imaging array or thelike), with a respective lens focusing images onto respective portionsof the array. The photosensor array may comprise a plurality ofphotosensor elements arranged in a photosensor array having rows andcolumns. Preferably, the imaging array has at least 300,000 photosensorelements or pixels, more preferably at least 500,000 photosensorelements or pixels and more preferably at least 1 million photosensorelements or pixels. The imaging array may capture color image data, suchas via spectral filtering at the array, such as via an RGB (red, greenand blue) filter or via a red/red complement filter or such as via anRCC (red, clear, clear) filter or the like. The logic and controlcircuit of the imaging sensor may function in any known manner, and theimage processing and algorithmic processing may comprise any suitablemeans for processing the images and/or image data.

For example, the vision system and/or processing and/or camera and/orcircuitry may utilize aspects described in U.S. Pat. Nos. 7,005,974;5,760,962; 5,877,897; 5,796,094; 5,949,331; 6,222,447; 6,302,545;6,396,397; 6,498,620; 6,523,964; 6,611,202; 6,201,642; 6,690,268;6,717,610; 6,757,109; 6,802,617; 6,806,452; 6,822,563; 6,891,563;6,946,978; 7,859,565; 5,550,677; 5,670,935; 6,636,258; 7,145,519;7,161,616; 7,230,640; 7,248,283; 7,295,229; 7,301,466; 7,592,928;7,881,496; 7,720,580; 7,038,577; 6,882,287; 5,929,786 and/or 5,786,772,which are all hereby incorporated herein by reference in theirentireties. The system may communicate with other communication systemsvia any suitable means, such as by utilizing aspects of the systemsdescribed in International Publication Nos. WO 2010/144900; WO2013/043661 and/or WO 2013/081985, and/or U.S. Pat. No. 9,126,525, whichare hereby incorporated herein by reference in their entireties.

The imaging device and control and image processor and any associatedillumination source, if applicable, may comprise any suitablecomponents, and may utilize aspects of the cameras and vision systemsdescribed in U.S. Pat. Nos. 5,550,677; 5,877,897; 6,498,620; 5,670,935;5,796,094; 6,396,397; 6,806,452; 6,690,268; 7,005,974; 7,937,667;7,123,168; 7,004,606; 6,946,978; 7,038,577; 6,353,392; 6,320,176;6,313,454 and/or 6,824,281, and/or International Publication Nos. WO2010/099416; WO 2011/02868 and/or WO 2013/016409, and/or U.S. Pat.Publication No. US 2010-0020170, which are all hereby incorporatedherein by reference in their entireties. The camera or cameras maycomprise any suitable cameras or imaging sensors or camera modules, andmay utilize aspects of the cameras or sensors described in U.S.Publication No. US-2009-0244361 and/or U.S. Pat. Nos. 8,542,451;7,965,336 and/or 7,480,149, which are hereby incorporated herein byreference in their entireties. The imaging array sensor may comprise anysuitable sensor, and may utilize various imaging sensors or imagingarray sensors or cameras or the like, such as a CMOS imaging arraysensor, a CCD sensor or other sensors or the like, such as the typesdescribed in U.S. Pat. Nos. 5,550,677; 5,670,935; 5,760,962; 5,715,093;5,877,897; 6,922,292; 6,757,109; 6,717,610; 6,590,719; 6,201,642;6,498,620; 5,796,094; 6,097,023; 6,320,176; 6,559,435; 6,831,261;6,806,452; 6,396,397; 6,822,563; 6,946,978; 7,339,149; 7,038,577;7,004,606; 7,720,580 and/or 7,965,336, and/or International PublicationNos. WO 2009/036176 and/or WO 2009/046268, which are all herebyincorporated herein by reference in their entireties.

The camera module and circuit chip or board and imaging sensor may beimplemented and operated in connection with various vehicularvision-based systems, and/or may be operable utilizing the principles ofsuch other vehicular systems, such as a vehicle headlamp control system,such as the type disclosed in U.S. Pat. Nos. 5,796,094; 6,097,023;6,320,176; 6,559,435; 6,831,261; 7,004,606; 7,339,149 and/or 7,526,103,which are all hereby incorporated herein by reference in theirentireties, a rain sensor, such as the types disclosed in commonlyassigned U.S. Pat. Nos. 6,353,392; 6,313,454; 6,320,176 and/or7,480,149, which are hereby incorporated herein by reference in theirentireties, a vehicle vision system, such as a forwardly, sidewardly orrearwardly directed vehicle vision system utilizing principles disclosedin U.S. Pat. Nos. 5,550,677; 5,670,935; 5,760,962; 5,877,897; 5,949,331;6,222,447; 6,302,545; 6,396,397; 6,498,620; 6,523,964; 6,611,202;6,201,642; 6,690,268; 6,717,610; 6,757,109; 6,802,617; 6,806,452;6,822,563; 6,891,563; 6,946,978 and/or 7,859,565, which are all herebyincorporated herein by reference in their entireties, a trailer hitchingaid or tow check system, such as the type disclosed in U.S. Pat. No.7,005,974, which is hereby incorporated herein by reference in itsentirety, a reverse or sideward imaging system, such as for a lanechange assistance system or lane departure warning system or for a blindspot or object detection system, such as imaging or detection systems ofthe types disclosed in U.S. Pat. Nos. 7,881,496; 7,720,580; 7,038,577;5,929,786 and/or 5,786,772, which are hereby incorporated herein byreference in their entireties, a video device for internal cabinsurveillance and/or video telephone function, such as disclosed in U.S.Pat. Nos. 5,760,962; 5,877,897; 6,690,268 and/or 7,370,983, and/or U.S.Publication No. US-2006-0050018, which are hereby incorporated herein byreference in their entireties, a traffic sign recognition system, asystem for determining a distance to a leading or trailing vehicle orobject, such as a system utilizing the principles disclosed in U.S. Pat.Nos. 6,396,397 and/or 7,123,168, which are hereby incorporated herein byreference in their entireties, and/or the like.

Optionally, the circuit board or chip may include circuitry for theimaging array sensor and or other electronic accessories or features,such as by utilizing compass-on-a-chip or EC driver-on-a-chip technologyand aspects such as described in U.S. Pat. Nos. 7,255,451 and/or7,480,149 and/or U.S. Publication Nos. US-2006-0061008 and/orUS-2010-0097469, which are hereby incorporated herein by reference intheir entireties.

Optionally, the vision system may include a display for displayingimages captured by one or more of the imaging sensors for viewing by thedriver of the vehicle while the driver is normally operating thevehicle. Optionally, for example, the vision system may include a videodisplay device disposed at or in the interior rearview mirror assemblyof the vehicle, such as by utilizing aspects of the video mirror displaysystems described in U.S. Pat. No. 6,690,268 and/or U.S. Publication No.US-2012-0162427, which are hereby incorporated herein by reference intheir entireties. The video mirror display may comprise any suitabledevices and systems and optionally may utilize aspects of the compassdisplay systems described in U.S. Pat. Nos. 7,370,983; 7,329,013;7,308,341; 7,289,037; 7,249,860; 7,004,593; 4,546,551; 5,699,044;4,953,305; 5,576,687; 5,632,092; 5,677,851; 5,708,410; 5,737,226;5,802,727; 5,878,370; 6,087,953; 6,173,508; 6,222,460; 6,513,252 and/or6,642,851, and/or European patent application, published Oct. 11, 2000under Publication No. EP 0 1043566, and/or U.S. Publication No.US-2006-0061008, which are all hereby incorporated herein by referencein their entireties. Optionally, the video mirror display screen ordevice may be operable to display images captured by a rearward viewingcamera of the vehicle during a reversing maneuver of the vehicle (suchas responsive to the vehicle gear actuator being placed in a reversegear position or the like) to assist the driver in backing up thevehicle, and optionally may be operable to display the compass headingor directional heading character or icon when the vehicle is notundertaking a reversing maneuver, such as when the vehicle is beingdriven in a forward direction along a road (such as by utilizing aspectsof the display system described in International Publication No. WO2012/051500, which is hereby incorporated herein by reference in itsentirety).

Optionally, the vision system (utilizing the forward facing camera and arearward facing camera and other cameras disposed at the vehicle withexterior fields of view) may be part of or may provide a display of atop-down view or birds-eye view system of the vehicle or a surround viewat the vehicle, such as by utilizing aspects of the vision systemsdescribed in International Publication Nos. WO 2010/099416; WO2011/028686; WO 2012/075250; WO 2013/019795; WO 2012/075250; WO2012/145822; WO 2013/081985; WO 2013/086249 and/or WO 2013/109869, whichare hereby incorporated herein by reference in their entireties.

Changes and modifications in the specifically described embodiments canbe carried out without departing from the principles of the invention,which is intended to be limited only by the scope of the appendedclaims, as interpreted according to the principles of patent lawincluding the doctrine of equivalents.

1. A method for estimating distance to an object via a vehicular visionsystem, the method comprising: disposing a camera at a rear portion of avehicle so as to view at least rearward of the vehicle, wherein thecamera comprises a pixelated imaging array having a plurality ofphotosensing elements; providing an electronic control unit (ECU)comprising an image processor operable to process image data captured bythe camera; capturing multiple frames of image data via the camera whilethe vehicle is moving; providing captured frames of image data to theECU; processing via the image processor provided captured frames ofimage data to determine a three dimensional object present in a field ofview of the camera; determining a point of interest on the determinedobject by processing via the image processor provided captured frames ofimage data while the vehicle is moving relative to the determinedobject; determining, by processing via the image processor of multipleprovided captured frames of image data while the vehicle is movingrelative to the determined object, and using triangulation based on thedetermined point of interest present in multiple provided capturedframes of image data, an estimated location in three dimensional spaceof the determined point of interest relative to the vehicle; andestimating distance to the estimated location in three dimensional spaceof the determined point of interest on the determined object bycomparing, one to another, provided captured frames of image data wherethere is movement of the determined point of interest of the determinedobject relative to the camera disposed at the vehicle.
 2. The method ofclaim 1, wherein determined points of interest in two or more providedcaptured frames of image data are compared to determine if they match.3. The method of claim 1, wherein determining the point of interest onthe determined object comprises detecting points of interest in two ormore provided captured frames of image data and performingcorrespondence analysis to find matched point pairs in the two or moreprovided captured frames of image data.
 4. The method of claim 1,comprising utilizing triangulation to determine an initial location of adetermined point of interest from a corresponding pair of determinedpoints of interest in first and second provided captured frames of imagedata.
 5. The method of claim 4, comprising processing via the imageprocessor a third provided captured frame of image data to refine thedetermined initial location of the point of interest.
 6. The method ofclaim 1, wherein the camera comprises a wide angle lens, and wherein thecamera, when disposed at the vehicle, has a wide angle field of viewexterior of the vehicle.
 7. The method of claim 1, comprising,responsive to the determined estimated location in three dimensionalspace of the determined point of interest, processing via the imageprocessor additional provided captured frames of image data to enhancethe estimation of the location in three dimensional space of thedetermined point of interest.
 8. The method of claim 7, comprising,responsive to processing via the image processor of provided capturedframes of image data, (a) refining correspondent feature locations bycomparing similarities between projected and detected points ofinterest, (b) selecting corresponding features according to theirdetermined similarities and (c) repeating triangulation on newlyselected corresponding pairs of determined points of interest.
 9. Themethod of claim 7, comprising repeating processing via the imageprocessor of additional provided captured frames of image data toenhance the estimated location in three dimensional space of thedetermined point of interest until a difference between subsequentestimations is less than a threshold level.
 10. A method for estimatingdistance to an object via a vehicular vision system, the methodcomprising: disposing a camera at a vehicle so as to view exterior ofthe vehicle, wherein the camera comprises a pixelated imaging arrayhaving a plurality of photosensing elements; wherein the cameracomprises a wide angle lens, and wherein the camera, when disposed atthe vehicle, has a wide angle field of view exterior of the vehicle;providing an electronic control unit (ECU) comprising an image processoroperable to process image data captured by the camera; capturingmultiple frames of image data via the camera while the vehicle ismoving; providing captured frames of image data to the ECU; processingvia the image processor provided captured frames of image data todetermine a three dimensional object present in a field of view of thecamera; determining a point of interest on the determined object byprocessing via the image processor provided captured frames of imagedata while the vehicle is moving relative to the determined object;wherein determined points of interest in two or more provided capturedframes of image data are compared to determine if they match;determining, by processing via the image processor of multiple providedcaptured frames of image data while the vehicle is moving relative tothe determined object, and using triangulation based on the determinedpoint of interest present in multiple provided captured frames of imagedata, an estimated location in three dimensional space of the determinedpoint of interest relative to the vehicle; and estimating distance tothe estimated location in three dimensional space of the determinedpoint of interest on the determined object by comparing, one to another,provided captured frames of image data where there is movement of thedetermined point of interest of the determined object relative to thecamera disposed at the vehicle.
 11. The method of claim 10, comprisingutilizing triangulation to determine an initial location of a determinedpoint of interest from a corresponding pair of determined points ofinterest in first and second provided captured frames of image data. 12.The method of claim 11, comprising processing via the image processor athird provided captured frame of image data to refine the determinedinitial location of the point of interest.
 13. The method of claim 10,comprising, responsive to the determined estimated location in threedimensional space of the determined point of interest, processing viathe image processor additional provided captured frames of image data toenhance the estimation of the location in three dimensional space of thedetermined point of interest.
 14. The method of claim 13, comprising,responsive to processing via the image processor of provided capturedframes of image data, (a) refining correspondent feature locations bycomparing similarities between projected and detected points ofinterest, (b) selecting corresponding features according to theirdetermined similarities and (c) repeating triangulation on newlyselected corresponding pairs of determined points of interest.
 15. Themethod of claim 13, comprising repeating processing via the imageprocessor of additional provided captured frames of image data toenhance the estimated location in three dimensional space of thedetermined point of interest until a difference between subsequentestimations is less than a threshold level.
 16. A method for estimatingdistance to an object via a vehicular vision system, the methodcomprising: disposing a camera at a vehicle so as to view exterior ofthe vehicle, wherein the camera comprises a pixelated imaging arrayhaving a plurality of photosensing elements; wherein the cameracomprises a wide angle lens, and wherein the camera, when disposed atthe vehicle, has a wide angle field of view exterior of the vehicle;providing an electronic control unit (ECU) comprising an image processoroperable to process image data captured by the camera; capturingmultiple frames of image data via the camera while the vehicle ismoving; providing captured frames of image data to the ECU; processingvia the image processor provided captured frames of image data todetermine a three dimensional object present in a field of view of thecamera; determining a point of interest on the determined object byprocessing via the image processor provided captured frames of imagedata while the vehicle is moving relative to the determined object;wherein determining the point of interest on the determined objectcomprises detecting points of interest in two or more provided capturedframes of image data and performing correspondence analysis to findmatched point pairs in the two or more provided captured frames of imagedata; determining, by processing via the image processor of multipleprovided captured frames of image data while the vehicle is movingrelative to the determined object, and using triangulation based on thedetermined point of interest present in multiple provided capturedframes of image data, an estimated location in three dimensional spaceof the determined point of interest relative to the vehicle; andestimating distance to the estimated location in three dimensional spaceof the determined point of interest on the determined object bycomparing, one to another, provided captured frames of image data wherethere is movement of the determined point of interest of the determinedobject relative to the camera disposed at the vehicle.
 17. The method ofclaim 16, comprising utilizing triangulation to determine an initiallocation of a determined point of interest from a corresponding pair ofdetermined points of interest in first and second provided capturedframes of image data, and comprising processing via the image processora third provided captured frame of image data to refine the determinedinitial location of the point of interest.
 18. The method of claim 16,comprising, responsive to the determined estimated location in threedimensional space of the determined point of interest, processing viathe image processor additional provided captured frames of image data toenhance the estimation of the location in three dimensional space of thedetermined point of interest.
 19. The method of claim 18, comprising,responsive to processing via the image processor of provided capturedframes of image data, (a) refining correspondent feature locations bycomparing similarities between projected and detected points ofinterest, (b) selecting corresponding features according to theirdetermined similarities and (c) repeating triangulation on newlyselected corresponding pairs of determined points of interest.
 20. Themethod of claim 18, comprising repeating processing via the imageprocessor of additional provided captured frames of image data toenhance the estimated location in three dimensional space of thedetermined point of interest until a difference between subsequentestimations is less than a threshold level.